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arXiv · 2605.18337

Infini-News: Efficiently Queryable Access to 1.3 Billion Processed Common Crawl News Articles

Ruggero Marino Lazzaroni·Jana Lasser·Kirill Solovev
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Abstract

Large-scale news corpora support a wide range of research in Computational Social Science and NLP, yet access remains constrained: commercial archives impose prohibitive costs and licensing restrictions, while open alternatives like Common Crawl's CC-News require terabyte-scale storage and computationally intensive processing. We present Infini-News, a retrieval toolkit and index for the entire CC-News archive from August 2016 to the latest available snapshot. Our contributions are threefold. First, we extract, clean the text, and parse the structured metadata of over 1.35B articles. Second, we enrich the corpus with language detection using three frontier language classifiers (GlotLID, lingua, and CommonLingua), and with multi-source geographic attribution that resolves a country of origin for 83.4% of articles across 222 countries. Third, we construct Infini-gram indexes: suffix-array structures that let researchers search the full archive for arbitrary text patterns in sub-second time. Together, these resources lower the barrier to longitudinal, cross-national media research.

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Ruggero Marino Lazzaroni, Jana Lasser, Kirill Solovev. 2026-05-18. Infini-News: Efficiently Queryable Access to 1.3 Billion Processed Common Crawl News Articles. https://arxiv.org/abs/2605.18337

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